class_docstr: this class is a dataset for testing registration algorithm on the Kaist urban dataset
  https://irap.kaist.ac.kr/dataset/
  as defined in https://github.com/iralabdisco/point_clouds_registration_benchmark.
class_docstr_tok: ["this","class","is","a","dataset","for","testing","registration","algorithm","on","the","Kaist","urban","dataset","https",":","\/\/irap.kaist.ac.kr\/dataset\/","as","defined","in","https",":","\/\/github.com\/iralabdisco\/point_clouds_registration_benchmark","."]
code: def __init__(self, dataset_opt):
      super().__init__(dataset_opt)
      pre_transform = self.pre_transform
      train_transform = self.train_transform
      ss_transform = getattr(self, "ss_transform", None)
      test_transform = self.test_transform
  
      # training is similar to test but only unsupervised training is allowed XD
      self.train_dataset = TestPairKaist(
          root=self._data_path,
          pre_transform=pre_transform,
          transform=train_transform,
          max_dist_overlap=dataset_opt.max_dist_overlap,
          self_supervised=True,
          min_size_block=dataset_opt.min_size_block,
          max_size_block=dataset_opt.max_size_block,
          num_pos_pairs=dataset_opt.num_pos_pairs,
          min_points=dataset_opt.min_points,
          ss_transform=ss_transform,
          use_fps=dataset_opt.use_fps,
      )
      self.test_dataset = TestPairKaist(
          root=self._data_path,
          pre_transform=pre_transform,
          transform=test_transform,
          max_dist_overlap=dataset_opt.max_dist_overlap,
          num_pos_pairs=dataset_opt.num_pos_pairs,
          self_supervised=False,
      )
  
file_path: torch-points3d/torch_points3d/datasets/registration/testkaist.py
imports: import gdown
  import os
  import logging
  import sys
  from zipfile import ZipFile
  from torch_points3d.datasets.registration.basetest import BasePCRBTest
  from torch_points3d.datasets.base_dataset import BaseDataset
  from torch_points3d.datasets.registration.base_siamese_dataset import BaseSiameseDataset
  from torch_points3d.datasets.registration.utils import files_exist
  from torch_points3d.datasets.registration.utils import makedirs
label_desc: Use image node_id 1 to create a new KaistDataset object from inherited base classes: BaseSiameseDataset with example: obj = KaistDataset(dataset_opt)